Home / Services / Multi-modular enterprise knowledge base, drawings and audio-visual RAG development
PROFESSIONAL SERVICE

Multimodal Enterprise Knowledge Base

When key knowledge is not only in Word and PDF, but is dispersed in scanning, equipment photographs, CAD export maps, audio recordings, training videos and operating forms, it is difficult for RAG to answer in full. Multimodular knowledge base needs to first identify structures, objects, time, version and permissions in different media, and then hand over recordable footage to the search and generation link.

Get graphic drawings and audio-visual knowledge to the U search portalAnswers can be returned to specific page, area or time segment checkReduced time for experts to repeat and interpret informationDevelopment of knowledge assets that can be updated, authorized and sustainable
Multi-modular enterprise knowledge base connects document drawings with graphic audio and video

Problems that enterprises usually face

Key fields in scanned, complex tables and drawings cannot be stabilized

The text description, pictures, videos and version records of the same product are scattered

Audio and video transcribing has a time axis but cannot be linked to original clips, speakers and information

Models can describe pictures without source, authority and professional terminology

After the MMA update, the search and answer quality is not fixed and retraceable

Our core services

01

Document layout, tables, OCR, pictures, drawings, audio and video content resolution

02

Uniform index for objects, chapters, page numbers, time code, versions and business primary keys

03

Text, visual and metadata mix search, reordering and cross-media references

04

Project, department, product, equipment and documentation-level filtering and audit

05

Answers quote original text, original image region or audio-visual time clips and support looking back

06

Multi-modular task sets, recall, quote, answer and rejection rating

07

Incremental Sync, Version Back, Knowledge Operation and Private deproyment

PROJECT DECISION PATH

Continue to judge in the context of current projects

The service boundaries, budget bases and modalities of implementation for different phases of the project are not identical and can be further assessed in conjunction with the following.

Project deliverables

The final delivery boundaries are defined according to the scope of services, the construction phase and the modalities of cooperation, and are described below as common results.

DELIVERABLEMulti-modular knowledge sources, formats, quality and authorized inventories
DELIVERABLEData resolution, splits, indexing and sync rules
DELIVERABLEKnowledge retrieval and question and answer applications and back-office source management
DELIVERABLEAuthority matrix, reference retroactive and audit log design
DELIVERABLEReal set of questions and multiple-modular quality assessment reports
DELIVERABLEDeployment, monitoring, data updating and operations manual

How the project budget is assessed

Service scope and business closed loops that must be completed in the first phase: document layout, tables, OCR, pictures, drawings, audio and video content resolution, objects, chapters, page numbers, time code, version and common index for business main key

Level of integrity of existing codes, data, systems, equipment and documents, and scope of coverage to be audited, relocated or re-engineered

Number of third-party interfaces, coordination responsibilities, data quality, unusual compensation and external supplier cooperation

Non-functional requirements such as performance, availability, security, authority, audit, compliance and access windows

Delivery depth and long-term responsibility: real problem set and multi-modular quality assessment reports, deployment, monitoring, data updating and operational manuals, and quality assurance, peacekeeping and continuous iterative scope

These circumstances do not recommend immediate initiation of full development.

Project objectives, responsible persons and acceptance criteria are not established

Key accounts, data, interfaces or business authorizations not available

Only the maximum price or very short cycle is sought, and the necessary tests and quality control are not accepted

IMPLEMENTATION PLAYBOOK

How multi-modular business knowledge base moves from demand to acceptable results

The following are used to explain the implementation methodology, the data calibre and the boundaries of responsibility, and are not used as a proxy for project judgement by functional lists.

Keywords and description of content

This page is organized around real service issues such as multimodule knowledge base, multimodular RAG, multimodular knowledge base development, drawings knowledge base. Keywords are used to help users and search systems identify themes, which do not represent commitments to fix effects; final scope, cycle, budget and indicators are based on project diagnosis, contract and acceptance baseline.

DELIVERY PATH

Implementation and delivery pathways

Each stage has clear objectives, participatory roles and assessable outcomes, and important decisions are not left to the end of the project.

01Selecting high-value knowledge tasks
02Inventory media format and data tenure
03Create a real set of questions and answers
04Verify parsing search and quoting PoC
05Access to identity privileges and business portals
06Greyscale upline and continuously re-measured
FAQ

FAQs

The most common issues before cooperation are clearly stated in advance.

What difference does a multimodular knowledge base make between a regular RAG?+

Normal RAGs are primarily dealing with text paragraphs, multimodular knowledge base, which also analyzes pictures, tables, drawings, audio and video, creates objects, locations, times, versions and permissions, and validates cross-media retrieval and citation.

Can the drawings and videos be uploaded directly and then used?+

Sample validation can be done first, but production construction usually requires clear formats, clarity, versions, professional terms, object connections and authorization.

How do you accept multimodular knowledge case?+

Data analysis, target clip recall, reference location, quality of answer, segregation of privileges, refusal, response time and updating should be checked separately for real questions, rather than just testing the chats.

DECISION FAQ

Common issues related to current projects

Check out all 265 questions.
Multi-modern knowledge base, AI audit and business continuity

What difference does a multi-modular knowledge base make between a regular RAG and a business?

If knowledge is mainly structured Word, PDF and web pages, ordinary text RAG is usually more economical. If key answers depend on photographic areas, complex tables, project drawings, audio or video clips, multimodular resolution, cross-media index and reversible references are required. Do not upgrade the concept of “multi-modular” directly, but check whether the text RAG is sufficient with real questions.

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Multi-modern knowledge base, AI audit and business continuity

What data do you need to build the drawings, pictures and audio-visual knowledge base?

The company should first prepare a sample of the document, version and object of the document in question, rather than moving it into the whole data at once. Each information should be related to the product, equipment, project, client, date, version, responsible department and access; the audio-visual record must also keep the time code and speaker, and the drawings need a clear format, layer and professional label.

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enterprise AI Effectiveness, Safety and Continued Operation

How do you want to sort the documents and data?

The document should clear duplicates and expired contents and keep title levels, table meanings and sources. The search is checked with real questions, not just whether the document is imported.

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enterprise AI Effectiveness, Safety and Continued Operation

Does the use of AI by companies reveal internal data?

Enterprises do have risks of data outage, over-authorization, log retention and third-party processing using AI, but they can be controlled through structures and systems. Instead of defaulting on uploading all information directly to public models, data should be disaggregated first. Sensitive scenes can be desensitive, access rights, proprietary networks or privatization models.

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